Eugene Belilovsky

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 86

Top Venues

CentraleSupélec, Châtenay-Malabry, France (PHD)

Education History

CentraleSupélec, Châtenay-Malabry, France

PHD

Publications

Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky
μLO: Compute-Efficient Meta-Generalization of Learned Optimizers. CoRR (2024)
AmirHossein Zamani, Amir G. Aghdam, Tiberiu Popa, Eugene Belilovsky
Temporally Consistent Object Editing in Videos using Extended Attention. CoRR (2024)
Stéphane Rivaud, Louis Fournier, Thomas Pumir, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
PETRA: Parallel End-to-end Training with Reversible Architectures. CoRR (2024)
Louis Fournier, Adel Nabli, Masih Aminbeidokhti, Marco Pedersoli, Eugene Belilovsky, Edouard Oyallon
WASH: Train your Ensemble with Communication-Efficient Weight Shuffling, then Average. CoRR (2024)
Adel Nabli, Louis Fournier, Pierre Erbacher, Louis Serrano, Eugene Belilovsky, Edouard Oyallon
ACCO: Accumulate while you Communicate, Hiding Communications in Distributed LLM Training. CoRR (2024)
Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky, Guy Wolf
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis. CoRR (2024)
Damien Martins Gomes, Yanlei Zhang, Eugene Belilovsky, Guy Wolf, Mahdi S. Hosseini
AdaFisher: Adaptive Second Order Optimization via Fisher Information. CoRR (2024)
Vaibhav Singh, Rahaf Aljundi, Eugene Belilovsky
Controlling Forgetting with Test-Time Data in Continual Learning. CoRR (2024)
Pedro Vianna, Muawiz Chaudhary, Paria Mehrbod, An Tang, Guy Cloutier, Guy Wolf, Michael Eickenberg, Eugene Belilovsky
Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation. CoRR (2024)
Géraldin Nanfack, Michael Eickenberg, Eugene Belilovsky
From Feature Visualization to Visual Circuits: Effect of Adversarial Model Manipulation. CoRR (2024)
Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish
Simple and Scalable Strategies to Continually Pre-train Large Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Géraldin Nanfack, Alexander Fulleringer, Jonathan Marty, Michael Eickenberg, Eugene Belilovsky
Adversarial Attacks on the Interpretation of Neuron Activation Maximization. AAAI (2024)
Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish
Simple and Scalable Strategies to Continually Pre-train Large Language Models. CoRR (2024)
Gwen Legate, Nicolas Bernier, Lucas Caccia, Edouard Oyallon, Eugene Belilovsky
Guiding The Last Layer in Federated Learning with Pre-Trained Models. CoRR (2023)
Nader Asadi, MohammadReza Davari, Sudhir Mudur, Rahaf Aljundi, Eugene Belilovsky
Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning. CoRR (2023)
Gwen Legate, Lucas Caccia, Eugene Belilovsky
Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning. CoLLAs (2023)
Gwen Legate, Lucas Caccia, Eugene Belilovsky
Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning. CoRR (2023)
Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Irina Rish, Eugene Belilovsky
Gradient Masked Averaging for Federated Learning. Trans. Mach. Learn. Res. 2023 (2023)
Tianhao Xie, Eugene Belilovsky, Sudhir Mudur, Tiberiu Popa
DragD3D: Vertex-based Editing for Realistic Mesh Deformations using 2D Diffusion Priors. CoRR (2023)
MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky
Reliability of CKA as a Similarity Measure in Deep Learning. ICLR (2023)
Nader Asadi, MohammadReza Davari, Sudhir Mudur, Rahaf Aljundi, Eugene Belilovsky
Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning. ICML (2023)
Gwen Legate, Nicolas Bernier, Lucas Page-Caccia, Edouard Oyallon, Eugene Belilovsky
Guiding The Last Layer in Federated Learning with Pre-Trained Models. NeurIPS (2023)
AmirMohammad Sarfi, Zahra Karimpour, Muawiz Chaudhary, Nasir Mohammad Khalid, Mirco Ravanelli, Sudhir Mudur, Eugene Belilovsky
Simulated Annealing in Early Layers Leads to Better Generalization. CoRR (2023)
Medric Sonwa, Johanna Hansen, Eugene Belilovsky
Imitation from Observation With Bootstrapped Contrastive Learning. CoRR (2023)
Adel Nabli, Eugene Belilovsky, Edouard Oyallon
: Accelerating Asynchronous Communication in Decentralized Deep Learning. CoRR (2023)
AmirMohammad Sarfi, Zahra Karimpour, Muawiz Chaudhary, Nasir Mohammad Khalid, Mirco Ravanelli, Sudhir Mudur, Eugene Belilovsky
Simulated Annealing in Early Layers Leads to Better Generalization. CVPR (2023)
Charles-Étienne Joseph, Benjamin Thérien, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky
Can We Learn Communication-Efficient Optimizers? CoRR (2023)
Adeetya Patel, Michael Eickenberg, Eugene Belilovsky
Local Learning with Neuron Groups. CoRR (2023)
Géraldin Nanfack, Alexander Fulleringer, Jonathan Marty, Michael Eickenberg, Eugene Belilovsky
Adversarial Attacks on the Interpretation of Neuron Activation Maximization. CoRR (2023)
Louis Fournier, Stéphane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Can Forward Gradient Match Backpropagation? CoRR (2023)
Adel Nabli, Eugene Belilovsky, Edouard Oyallon
: Accelerating Asynchronous Communication in Decentralized Deep Learning. NeurIPS (2023)
Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort
Continual Pre-Training of Large Language Models: How to (re)warm your model? CoRR (2023)
Louis Fournier, Stéphane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Can Forward Gradient Match Backpropagation? ICML (2023)
MohammadReza Davari, Eugene Belilovsky
Model Breadcrumbs: Scaling Multi-Task Model Merging with Sparse Masks. CoRR (2023)
Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Eugene Belilovsky, Irina Rish
Gradient Masked Averaging for Federated Learning. CoRR (2022)
MohammadReza Davari, Nader Asadi, Sudhir Mudur, Rahaf Aljundi, Eugene Belilovsky
Probing Representation Forgetting in Supervised and Unsupervised Continual Learning. CVPR (2022)
MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky
Reliability of CKA as a Similarity Measure in Deep Learning. CoRR (2022)
Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio
Towards Scaling Difference Target Propagation by Learning Backprop Targets. ICML (2022)
MohammadReza Davari, Nader Asadi, Sudhir Mudur, Rahaf Aljundi, Eugene Belilovsky
Probing Representation Forgetting in Supervised and Unsupervised Continual Learning. CoRR (2022)
Nader Asadi, Sudhir Mudur, Eugene Belilovsky
Tackling Online One-Class Incremental Learning by Removing Negative Contrasts. CoRR (2022)
Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky
New Insights on Reducing Abrupt Representation Change in Online Continual Learning. ICLR (2022)
Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio
Towards Scaling Difference Target Propagation by Learning Backprop Targets. CoRR (2022)
Nasir Mohammad Khalid, Tianhao Xie, Eugene Belilovsky, Tiberiu Popa
CLIP-Mesh: Generating textured meshes from text using pretrained image-text models. SIGGRAPH Asia (2022)
Moslem Yazdanpanah, Aamer Abdul Rahman, Muawiz Chaudhary, Christian Desrosiers, Mohammad Havaei, Eugene Belilovsky, Samira Ebrahimi Kahou
Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning. CVPR (2022)
Nasir Khalid, Tianhao Xie, Eugene Belilovsky, Tiberiu Popa
Text to Mesh Without 3D Supervision Using Limit Subdivision. CoRR (2022)
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
Parametric Scattering Networks. CVPR (2022)
Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods. CoRR (2021)
Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
Generative Compositional Augmentations for Scene Graph Prediction. ICCV (2021)
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
Parametric Scattering Networks. CoRR (2021)
Eugene Belilovsky, Louis Leconte, Lucas Caccia, Michael Eickenberg, Edouard Oyallon
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning. CoRR (2021)
Lucas Caccia, Rahaf Aljundi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky
Reducing Representation Drift in Online Continual Learning. CoRR (2021)
Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods. ICLR (2021)
Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
Learning Compositional Shape Priors for Few-Shot 3D Reconstruction. CoRR (2021)
Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg
Kymatio: Scattering Transforms in Python. J. Mach. Learn. Res. 21 (2020)
Mateusz Michalkiewicz, Eugene Belilovsky, Mahsa Baktashmotlagh, Anders P. Eriksson
A Simple and Scalable Shape Representation for 3D Reconstruction. CoRR (2020)
Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. CoRR (2020)
Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. ECCV (25) (2020)
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Decoupled Greedy Learning of CNNs. ICML (2020)
Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. BMVC (2020)
Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
Generative Graph Perturbations for Scene Graph Prediction. CoRR (2020)
Mateusz Michalkiewicz, Eugene Belilovsky, Mahsa Baktashmotlagh, Anders P. Eriksson
A Simple and Scalable Shape Representation for 3D Reconstruction. BMVC (2020)
Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau
Online Learned Continual Compression with Adaptive Quantization Modules. ICML (2020)
Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. CoRR (2020)
Catalina Cangea, Eugene Belilovsky, Pietro Liò, Aaron C. Courville
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. CoRR (2019)
Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau
Online Learned Continual Compression with Stacked Quantization Module. CoRR (2019)
Catalina Cangea, Eugene Belilovsky, Pietro Liò, Aaron C. Courville
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. ViGIL@NeurIPS (2019)
Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, Lucas Page-Caccia
Online Continual Learning with Maximal Interfered Retrieval. NeurIPS (2019)
Catalina Cangea, Eugene Belilovsky, Aaron C. Courville
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. BMVC (2019)
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Decoupled Greedy Learning of CNNs. CoRR (2019)
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Greedy Layerwise Learning Can Scale To ImageNet. ICML (2019)
Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Min Lin, Laurent Charlin, Tinne Tuytelaars
Online Continual Learning with Maximally Interfered Retrieval. CoRR (2019)
Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
Scattering Networks for Hybrid Representation Learning. IEEE Trans. Pattern Anal. Mach. Intell. 41 (9) (2019)
Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko, Michal Valko
Compressing the Input for CNNs with the First-Order Scattering Transform. ECCV (9) (2018)
Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg
Kymatio: Scattering Transforms in Python. CoRR (2018)
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Greedy Layerwise Learning Can Scale to ImageNet. CoRR (2018)
Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
Scattering Networks for Hybrid Representation Learning. CoRR (2018)
Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko, Michal Valko
Compressing the Input for CNNs with the First-Order Scattering Transform. CoRR (2018)
Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville
Blindfold Baselines for Embodied QA. CoRR (2018)
Eugene Belilovsky, Matthew B. Blaschko, Jamie Ryan Kiros, Raquel Urtasun, Richard S. Zemel
Joint Embeddings of Scene Graphs and Images. ICLR (Workshop) (2017)
Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko
Learning to Discover Sparse Graphical Models. ICLR (Workshop) (2017)
Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko
Scaling the Scattering Transform: Deep Hybrid Networks. CoRR (2017)
Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko
Scaling the Scattering Transform: Deep Hybrid Networks. ICCV (2017)
Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko
Learning to Discover Sparse Graphical Models. ICML (2017)
Wacha Bounliphone, Eugene Belilovsky, Matthew B. Blaschko, Ioannis Antonoglou, Arthur Gretton
A Test of Relative Similarity For Model Selection in Generative Models. ICLR (Poster) (2016)
Eugene Belilovsky, Gaël Varoquaux, Matthew B. Blaschko
Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity. NIPS (2016)
Wacha Bounliphone, Eugene Belilovsky, Arthur Tenenhaus, Ioannis Antonoglou, Arthur Gretton, Matthew B. Blaschko
Fast Non-Parametric Tests of Relative Dependency and Similarity. CoRR (2016)
Eugene Belilovsky, Katerina Gkirtzou, Michail Misyrlis, Anna B. Konova, Jean Honorio, Nelly Alia-Klein, Rita Z. Goldstein, Dimitris Samaras, Matthew B. Blaschko
Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm. Comput. Medical Imaging Graph. 46 (2015)
Eugene Belilovsky, Andreas Argyriou, Gaël Varoquaux, Matthew B. Blaschko
Convex relaxations of penalties for sparse correlated variables with bounded total variation. Mach. Learn. 100 (2-3) (2015)
Florian Müller, Eugene Belilovsky, Alfred Mertins
Generalized cyclic transformations in speaker-independent speech recognition. ASRU (2009)

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Publication Activity (10 Years)

Top Topics

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Eugene Belilovsky